Implementasi Decision Tree Untuk Prediksi Kelulusan Mahasiswa Tepat Waktu - Christin Nandari Dengen; Kusrini Kusrini; Emha Taufiq Luthfi (STMIK PONTIANAK, 2020)
Students who are accepted every year are increasing, but not all students can graduate on time. In achieving graduation, of course, there are stages or processes that must be passed by each student such as following a number of courses, conducting fieldwork practices, real work lectures and final assignment seminars. These processes are carried out within a period of time determined by the University. For this reason, a prediction system for student graduation is needed in order to minimize students who graduate not on time. In predicting student graduation on time using 50 sample data for the 2013 graduation year with gender, IPK, graduation and toefl attributes. This study carried out the application of the CRISP-DM method with the C4.5 algorithm in predicting student graduation. The use of the C4.5 algorithm is supported by simulations carried out using the WeKa application and gets an accuracy value of 60%. With the existence of this research, it is expected to be able to help the Informatics Engineering Program at Universita Mulawarman so that students can graduate on time.